Benutzer: Gast  Login
Titel:

Advantages of Hybrid Neural Network Architectures to Enhance Prediction of Tensile Properties in Laser Powder Bed Fusion

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Funcke, Florian; Forster, Tobias; Mayr, Peter
Abstract:
The properties of AlSi10Mg produced by Laser Powder Bed Fusion (PBF-LB) are defined by a multitude of different machine and laser parameters. This multi-parameter space presents the challenge of optimizing the material properties for a given application by the sheer amount of possible parameter combinations. Characterizing this multi-parameter space empirically is limited by time and resources and thus yields an incomplete picture of the process capabilities and local optima, respectively. To im...     »
Stichworte:
Additive Manufacturing, Neural Networks, Laser Powder Bed Fusion, Micrographs
Zeitschriftentitel:
Key Engineering Materials
Jahr:
2023
Band / Volume:
964
Seitenangaben Beitrag:
65-71
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.4028/p-0tcamf
WWW:
https://www.scientific.net/KEM.964.65
Verlag / Institution:
Trans Tech Publications, Ltd.
E-ISSN:
1662-9795
Eingereicht (bei Zeitschrift):
31.05.2023
Angenommen (von Zeitschrift):
31.08.2023
Publikationsdatum:
23.11.2023
 BibTeX